NAP (Nested Adaptive Prediction)

Nowadays data sizes increases, thus storage and security of data is very crucial. Huge companies pay billions of dollars for storage of data and this getting higher and higher every day. That means bigger investments and higher bandwidth.
This project the goal is to make prediction algorithm that is compatible with image ﬁles. Some scientiﬁc sources has been researched such as MED, GAP, LOCO-I, CALIC etc.). As a result, achievement of a success on expectations with algorithms that works on image files and known as standard algorithms, professional compression programs and algorithms that we developed in workings and experiments. It’s observed that the algorithms are more successful in complex images.